Observational Constraints on Warm Cloud Microphysical Processes Using Machine Learning and Optimization Techniques

We introduce new parameterizations for autoconversion and accretion rates that greatly improve representation of the growth processes of warm rain. The new parameterizations capitalize on machine‐learning and optimization techniques and are constrained by in situ cloud probe measurements from the re...

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Detalles Bibliográficos
Autores principales: Chiu, J. Christine, Yang, C. Kevin, van Leeuwen, Peter Jan, Feingold, Graham, Wood, Robert, Blanchard, Yann, Mei, Fan, Wang, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Research Letter
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7900997/
https://www.ncbi.nlm.nih.gov/pubmed/33678926
http://dx.doi.org/10.1029/2020GL091236

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7900997/
https://www.ncbi.nlm.nih.gov/pubmed/33678926
http://dx.doi.org/10.1029/2020GL091236

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